The chief aim of this grant is to establish a strategy to study complete transcription networks in animals. A fundamental challenge in the "post genome era" is to decipher the transcriptional information contained in the extensive cis-acting DNA sequences that direct intricate patterns of gene expression in complex organisms. We argue that these challenges cannot be fully met without a systematic characterization of all the components of the transcription regulatory network. The transcriptional network in the early Drosophila embryo is uniquely suited for such system-wide analyses because it offers powerful molecular and genetic tools, is relatively simple, and contains a known, tractable number of regulators. Using this system, we propose to develop methods and strategies to collect four essential classes of data and to use these data to develop bioinformatic analyses that predict which regulatory sequences transcription factors bind in vivo, the combinatorial code determining how factors interact once bound to promoters, and the patterns of expression driven by particular regulatory sequences. Throughout the project, the data collection methods will be refined and modified in response to our analysis of the data. Our specific aims are to: [unreadable] [unreadable] 1. Develop a strategy to obtain a new, more detailed understanding of the in vitro DNA binding specificities of transcription factors using a modified binding site selection protocol and other methods. [unreadable] [unreadable] 2. Optimize in vivo crosslinking and genomic microarrays to measure binding of endogenous factors to thousands of DNA elements in living embryos. [unreadable] [unreadable] 3. Develop advanced imaging methods to quantitate gene expression patterns in 3D with single cell resolution and use this information to identify transcription factor target genes. [unreadable] [unreadable] 4. Explore a novel transgenic promoter based strategy to test large numbers of predicted functional cis-regulatory sequences and determine the expression patterns they drive to aid future predictions. [unreadable] [unreadable] 5. Use engineering solutions to increase the throughout of Aims 1-4 to enable comprehensive analysis of not only the early Drosophila network, but also larger networks in other animals, including mammals. [unreadable] [unreadable] 6. Develop bioinformatic tools that utilize the data in Aims 1-4 to analyze the transcriptional network, and make the data and algorithms available to the community at large. [unreadable] [unreadable]